Structural equation modeling unifies regression, factor analysis, directed graphs and other (non)linear models into a powerful and flexible toolbox for statistical inference. It has well-documented merits in various areas, as diverse as biology, ecology, economics, psychology, and social sciences. Despite the flexibility of structural equation models (SEMs), their ability to cope with high-dimensional problems encountered in contemporary fields is limited due to the lack of efficient and effective inference methods. A truly focused effort is required to make necessary breakthroughs in high-dimensional SEMs and demonstrate their suitability in emerging research areas. The objective of this project is to develop efficient inference methods for high-dimensional SEMs tailored for inference of gene networks and optimized strategies for chemical genomics. A key enabler to this end is leveraging the sparsity attributes present in high-dimensional data. The proposed research themes are centered around two thrusts: (T1) Inference for sparse SEMs: A set of efficient and robust inference methods using novel algorithmic techniques and parallel computing will be developed for both linear and nonlinear high-dimensional SEMs; and (T2) SEM-based inference of gene regulatory networks and application to optimized chemical genomics: S. cerevisiae and human gene networks will be inferred by integrating multiple types of data under the SEM framework. The inferred networks will be also validated experimentally. A set of natural compounds will be profiled using SEM-based computational strategies to drive chemical genetic screens in S. cerevisiae and S. pombe. The proposed modeling framework will explicitly incorporate genetic variation across individuals in a population, and thus, can directly utilize the wealth of sequencing data that is currently being generated to tackle the genotype-to-phenotype challenge. Furthermore, the proposed work will markedly enhance the throughput at which new bioactive compounds are characterized using chemical genomics-based approaches in yeast, and in other model systems. It will also enable the application of high-dimensional SEMs in additional areas including economics, psychology, ecology, biobehavioral and other social science.

Public Health Relevance

Successful completion of the proposed project could have broad impact on human health as it would help to understand the role of genes and their interactions in various diseases and enable the construction of more comprehensive small molecule libraries with well-defined molecular targets for use in new therapeutics.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM104975-04
Application #
8839259
Study Section
Special Emphasis Panel (ZGM1-CBCB-5 (BM))
Program Officer
Brazhnik, Paul
Project Start
2012-07-01
Project End
2017-04-30
Budget Start
2015-05-01
Budget End
2016-04-30
Support Year
4
Fiscal Year
2015
Total Cost
$357,106
Indirect Cost
$59,316
Name
University of Miami Coral Gables
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
625174149
City
Coral Gables
State
FL
Country
United States
Zip Code
33146
Kuzmin, Elena; VanderSluis, Benjamin; Wang, Wen et al. (2018) Systematic analysis of complex genetic interactions. Science 360:
Bottoms, Scott; Dickinson, Quinn; McGee, Mick et al. (2018) Chemical genomic guided engineering of gamma-valerolactone tolerant yeast. Microb Cell Fact 17:5
Zhou, Xin; Chen, Zhibin; Cai, Xiaodong (2018) Identification of epigenetic modulators in human breast cancer by integrated analysis of DNA methylation and RNA-Seq data. Epigenetics 13:473-489
Adnani, Navid; Chevrette, Marc G; Adibhatla, Srikar N et al. (2017) Coculture of Marine Invertebrate-Associated Bacteria and Interdisciplinary Technologies Enable Biosynthesis and Discovery of a New Antibiotic, Keyicin. ACS Chem Biol 12:3093-3102
Piotrowski, Jeff S; Li, Sheena C; Deshpande, Raamesh et al. (2017) Functional annotation of chemical libraries across diverse biological processes. Nat Chem Biol 13:982-993
Davison, Jack R; Lohith, Katheryn M; Wang, Xiaoning et al. (2017) A New Natural Product Analog of Blasticidin S Reveals Cellular Uptake Facilitated by the NorA Multidrug Transporter. Antimicrob Agents Chemother 61:
Wyche, Thomas P; Alvarenga, René F Ramos; Piotrowski, Jeff S et al. (2017) Chemical Genomics, Structure Elucidation, and in Vivo Studies of the Marine-Derived Anticlostridial Ecteinamycin. ACS Chem Biol 12:2287-2295
Morales, Eduardo H; Pinto, Camilo A; Luraschi, Roberto et al. (2017) Accumulation of heme biosynthetic intermediates contributes to the antibacterial action of the metalloid tellurite. Nat Commun 8:15320
Berberidis, Dimitris; Kekatos, Vassilis; Giannakis, Georgios B (2016) Online Censoring for Large-Scale Regressions with Application to Streaming Big Data. IEEE Trans Signal Process 64:3854-3867
Dickinson, Quinn; Bottoms, Scott; Hinchman, Li et al. (2016) Mechanism of imidazolium ionic liquids toxicity in Saccharomyces cerevisiae and rational engineering of a tolerant, xylose-fermenting strain. Microb Cell Fact 15:17

Showing the most recent 10 out of 19 publications